際際滷shows by User: Anunaya / http://www.slideshare.net/images/logo.gif 際際滷shows by User: Anunaya / Wed, 29 Oct 2014 00:28:17 GMT 際際滷Share feed for 際際滷shows by User: Anunaya Survey on article extraction and comment monitoring techniques /slideshow/survey-on-article-extraction-and-comment-monitoring-techniques-40852527/40852527 surveyonarticleextractionandcommentmonitoringtechniques-141029002817-conversion-gate01
The online News publisher publishes their news in the form of articles. Most of the online news websites provide the facility for their users to comment on the news article and as a result a lot of people comment on the news article. Hence news web page contains huge data in the form of article content and comments data, etc and have a good potential to be a resource for many Information Retrieval Systems and Data Mining Applications. The extraction of the main content (Article content) from a web page has always been a challenging task because a web page contains other information like advertisements and hyperlinks etc. which is not related to Article Text. In this survey, we review various techniques which are proposed by various researchers to extract the article content from a news web site. We also learn various techniques which monitor and analyze the comments for various applications like popularity prediction of articles and identification of discussions thread in the comments data.]]>
The online News publisher publishes their news in the form of articles. Most of the online news websites provide the facility for their users to comment on the news article and as a result a lot of people comment on the news article. Hence news web page contains huge data in the form of article content and comments data, etc and have a good potential to be a resource for many Information Retrieval Systems and Data Mining Applications. The extraction of the main content (Article content) from a web page has always been a challenging task because a web page contains other information like advertisements and hyperlinks etc. which is not related to Article Text. In this survey, we review various techniques which are proposed by various researchers to extract the article content from a news web site. We also learn various techniques which monitor and analyze the comments for various applications like popularity prediction of articles and identification of discussions thread in the comments data.]]> Wed, 29 Oct 2014 00:28:17 GMT /slideshow/survey-on-article-extraction-and-comment-monitoring-techniques-40852527/40852527 Anunaya@slideshare.net(Anunaya) Survey on article extraction and comment monitoring techniques Anunaya The online News publisher publishes their news in the form of articles. Most of the online news websites provide the facility for their users to comment on the news article and as a result a lot of people comment on the news article. Hence news web page contains huge data in the form of article content and comments data, etc and have a good potential to be a resource for many Information Retrieval Systems and Data Mining Applications. The extraction of the main content (Article content) from a web page has always been a challenging task because a web page contains other information like advertisements and hyperlinks etc. which is not related to Article Text. In this survey, we review various techniques which are proposed by various researchers to extract the article content from a news web site. We also learn various techniques which monitor and analyze the comments for various applications like popularity prediction of articles and identification of discussions thread in the comments data. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/surveyonarticleextractionandcommentmonitoringtechniques-141029002817-conversion-gate01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> The online News publisher publishes their news in the form of articles. Most of the online news websites provide the facility for their users to comment on the news article and as a result a lot of people comment on the news article. Hence news web page contains huge data in the form of article content and comments data, etc and have a good potential to be a resource for many Information Retrieval Systems and Data Mining Applications. The extraction of the main content (Article content) from a web page has always been a challenging task because a web page contains other information like advertisements and hyperlinks etc. which is not related to Article Text. In this survey, we review various techniques which are proposed by various researchers to extract the article content from a news web site. We also learn various techniques which monitor and analyze the comments for various applications like popularity prediction of articles and identification of discussions thread in the comments data.
Survey on article extraction and comment monitoring techniques from Anunaya
]]> 1220 6 https://cdn.slidesharecdn.com/ss_thumbnails/surveyonarticleextractionandcommentmonitoringtechniques-141029002817-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Generating Storylines (Literature Survey) /slideshow/generating-storylinesliterature-survey/40836538 seminarppt-141028145018-conversion-gate01
Today there is vast amount of information present on the internet. There are a number of news media, blogs, social networks like Facebook, Google Plus etc. and microblogs such as Twitter that provide information to the user who is trying to extract some specific knowledge from the world wide web. Thus the user gets burdened with large amount of data which makes it difficult for the user to find the desired information. In this seminar report, we discuss the various techniques that are used to represent data in a more meaningful manner to counter the problem of Information Overload. We focus primarily on various algorithms used for Storyline Generation which is a technique to capture the underlying temporal and casual dependencies amongst the news events.]]>
Today there is vast amount of information present on the internet. There are a number of news media, blogs, social networks like Facebook, Google Plus etc. and microblogs such as Twitter that provide information to the user who is trying to extract some specific knowledge from the world wide web. Thus the user gets burdened with large amount of data which makes it difficult for the user to find the desired information. In this seminar report, we discuss the various techniques that are used to represent data in a more meaningful manner to counter the problem of Information Overload. We focus primarily on various algorithms used for Storyline Generation which is a technique to capture the underlying temporal and casual dependencies amongst the news events.]]> Tue, 28 Oct 2014 14:50:18 GMT /slideshow/generating-storylinesliterature-survey/40836538 Anunaya@slideshare.net(Anunaya) Generating Storylines (Literature Survey) Anunaya Today there is vast amount of information present on the internet. There are a number of news media, blogs, social networks like Facebook, Google Plus etc. and microblogs such as Twitter that provide information to the user who is trying to extract some specific knowledge from the world wide web. Thus the user gets burdened with large amount of data which makes it difficult for the user to find the desired information. In this seminar report, we discuss the various techniques that are used to represent data in a more meaningful manner to counter the problem of Information Overload. We focus primarily on various algorithms used for Storyline Generation which is a technique to capture the underlying temporal and casual dependencies amongst the news events. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/seminarppt-141028145018-conversion-gate01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Today there is vast amount of information present on the internet. There are a number of news media, blogs, social networks like Facebook, Google Plus etc. and microblogs such as Twitter that provide information to the user who is trying to extract some specific knowledge from the world wide web. Thus the user gets burdened with large amount of data which makes it difficult for the user to find the desired information. In this seminar report, we discuss the various techniques that are used to represent data in a more meaningful manner to counter the problem of Information Overload. We focus primarily on various algorithms used for Storyline Generation which is a technique to capture the underlying temporal and casual dependencies amongst the news events.
Generating Storylines (Literature Survey) from Anunaya
]]> 1312 7 https://cdn.slidesharecdn.com/ss_thumbnails/seminarppt-141028145018-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://public.slidesharecdn.com/v2/images/profile-picture.png https://cdn.slidesharecdn.com/ss_thumbnails/surveyonarticleextractionandcommentmonitoringtechniques-141029002817-conversion-gate01-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/survey-on-article-extraction-and-comment-monitoring-techniques-40852527/40852527 Survey on article extr... https://cdn.slidesharecdn.com/ss_thumbnails/seminarppt-141028145018-conversion-gate01-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/generating-storylinesliterature-survey/40836538 Generating Storylines ...